For as long as retailers have been selling products and services, they have been seeking ways to increase profits. Accordingly, many retailers create new initiatives that they believe will have a positive impact on profits. These initiatives usually cover various aspects of business operations that drive profits. For example, retailers may change product prices, move products to different locations of a sales floor, change the amount of space allocated to each product, test new products, add or reduce sales staff, introduce new concepts (e.g., in-store kiosks), remodel older stores, and test new marketing campaigns. Retailers may test these new initiatives in selected test locations (i.e., certain stores) and subsequently determine whether to introduce the initiatives to remaining business locations based on the success of the initiatives at the selected test locations. Historically, retailer managers have used business instinct and/or anecdotal evidence to assess the success of the initiatives in order to make a decision whether to implement the initiatives at the rest of its business locations.
In recent years, however, some retailers have become more structured and analytical in their set up and analysis of tests. These retailers collect performance metrics, such as sales and gross profit data from the test locations and analyze the data using conventional software products, such as spreadsheet or statistical software packages. Retailers may measure the change in the performance metrics at the locations that introduced the new initiatives relative to a change in the same metrics at a control group of locations that did not implement the initiatives. In doing so, the retailers attempt to identify the impact of the initiatives on the performance metrics in order to determine whether they provide a positive return on investment. Accordingly, these retailers can make an informed decision whether to extend the concept to remaining locations in a business network.
As retailers improve their approach in analyzing initiatives, they have increased the frequency and scope of the initiatives under test. Often, several functional teams associated with a retailer may independently design, execute, and analyze initiatives under consideration for implementation at the retailer's business locations. For example, a marketing team may test a new advertisement for a product in certain markets, while an operations team tests a new training initiative. At the same time, a merchandising team may be modifying product displays and a store development team may be remodeling the layout of the retailer's locations. Accordingly, it is becoming increasingly difficult to coordinate the analysis of initiatives among the several functional teams that may implement, or is implementing, one or more initiatives. The consequence is that teams are unaware that tests are run in the same location at the same time. This simultaneous testing affects the outcome regarding the actual impact a particular initiative may have at given location. For instance, an operations team may associate a significant sales increase in a particular test market to a recently executed training initiative without realizing that a marketing team had run additional advertising in the same market. Such concurrent testing may cause the operations team to over-estimate the impact of their testing training program and make inefficient decisions regarding whether to extend the training program to other markets.
Further, functional teams may find it increasingly difficult to communicate and coordinate with the retail locations actually implementing an initiative. For example, suppose that an operations team desires to test the impact of additional labor in a set of retail locations during a particular holiday season. Accordingly, the operations team may allocate a larger budget for the acquisition of additional labor for particular locations. The managers of these locations, however, still need to actually spend the allotted budget on additional labor. Any deviation from this purpose affects the outcome of the analysis of the initiative. Without tools to enable the execution of an initiative, functional teams may find it difficult to ensure that locations are aware of an initiative and are actually executing the initiative as proposed by the team.